A novel method predicts cancer and immune cell types from bulk tumor gene expression data with the ability to consider uncharacterized and possibly highly variable cell types, which is validated in human genome.
Nutrient limitation elicits differential responses in cells lacking the tumor suppressor PTEN and in normal cells, resulting in hyperplastic overgrowth of PTEN mutant tissue independent of additional mutations.
Tumor immunogenicity is quantified with a novel method, and the resulting tumor immunogenicity score is an effective tumor-inherent biomarker for prediction of response to immune checkpoint inhibitors.
Disrupting extrusion, a process that drives epithelial cell death, leads to increased cell survival, poor barrier function, and enhanced cell invasion and, thereby, promotes tumor initiation and progression.
The forces that multicellular tumor aggregates exert on their environment lead to non-linear, scale-invariant tissue deformations far away from the tumor, which can be exploited to quantify its collective contractility.
A library of the paired peptide/HLA multimers and artificial APCs allows for construction of a large database of class I-restricted peptides and cognate tumor-reactive TCR genes at an unprecedented scale.